Impact of Chronic Kidney Disease on In-Hospital and 3-Year Clinical Outcomes in Patients With Acute Myocardial Infarction Treated by Contemporary Percutaneous Coronary Intervention and Optimal Medical Therapy　― Insights From the J-MINUET Study ―

Abstract

Background: The impact of chronic kidney disease (CKD) on long-term outcomes following acute myocardial infarction (AMI) in the era of modern primary PCI with optimal medical therapy is still in debate.

Methods and Results: A total of 3,281 patients with AMI were enrolled in the J-MINUET registry, with primary PCI of 93.1% in STEMI. CKD stage on admission was classified into: no CKD (eGFR ≥60 mL/min/1.73 m²); moderate CKD (60>eGFR≥30 mL/min/1.73 m²); and severe CKD (eGFR <30 mL/min/1.73 m²). While the primary endpoint was all-cause mortality, the secondary endpoint was major adverse cardiac events (MACE), defined as a composite of all-cause death, cardiac failure, myocardial infarction (MI) and stroke. Of the 3,281 patients, 1,878 had no CKD, 1,073 had moderate CKD and 330 had severe CKD. Pre-person-days age- and sex-adjusted in-hospital mortality significantly increased from 0.014% in no CKD through 0.042% in moderate CKD to 0.084% in severe CKD (P<0.0001). Three-year mortality and MACE significantly deteriorated from 5.09% and 15.8% in no CKD through 16.3% and 38.2% in moderate CKD to 36.7% and 57.9% in severe CKD, respectively (P<0.0001). C-index significantly increased from the basic model of 0.815 (0.788–0.841) to 0.831 (0.806–0.857), as well as 0.731 (0.708–0.755) to 0.740 (0.717–0.764) when adding CKD stage to the basic model in predicting 3-year mortality (P=0.013; net reclassification improvement [NRI] 0.486, P<0.0001) and MACE (P=0.046; NRI 0.331, P<0.0001) respectively.

Conclusions: CKD remains a useful predictor of in-hospital and 3-year mortality as well as MACE after AMI in the modern PCI and optimal medical therapy era.

Chronic kidney disease (CKD) is known to be associated with adverse outcomes in patients presenting with acute myocardial infarction (AMI).^1–5 Serum creatinine is an important component of the GRACE score and similar scoring systems for the risk stratification of patients presenting with acute coronary syndromes.⁶ However, although these scoring systems have been derived from large robust multicenter international registry studies, these were conducted over a decade ago.⁶ It is unclear whether advances in both the availability and deployment of modern guideline-directed medical therapy, and especially greater access to mechanical reperfusion therapy using recent percutaneous coronary intervention (PCI) technology have altered outcomes in patients with CKD.^7–9 The status and importance of CKD as an independent risk factor for short- and long-term mortality and major adverse cardiac events after AMI in the modern era of primary PCI and recent advances in medical therapy therefore remains unresolved.

Editorial p ????

We evaluated the prognostic significance of CKD on in-hospital and 3-year cardiovascular outcomes in a large contemporary registry cohort; the Japanese MINUET study.^10,11 In particular, we sought to determine the independent impact of renal dysfunction on short- and long-term adverse outcomes after AMI relative to potential confounding-associated cardiovascular risk factors.

Methods

Study Design and Subjects

The J-MINUET is a prospective observational multicenter study (UMIN000010037). Consecutive patients hospitalized within 48 h of onset of AMI at 28 Japanese medical institutions were enrolled between July 2013 and May 2014.^10,11 Diagnosis of AMI was based on the ESC/ACC Foundation (ACCF)/American Heart Association (AHA)/World Heart Federation Task Force for the Universal Definition of Myocardial Infarction.¹²

Only type 1 AMI (spontaneous MI related to ischemia from a primary coronary event) and type 2 (MI secondary to ischemia because of either increased oxygen demand or decreased supply) were included in this registry. In brief, AMI was diagnosed by the rise and/or fall of cardiac biomarkers (preferred: troponin) with at least 1 value above the 99th percentile of the upper reference limit observed together with evidence of myocardial ischemia with at least one of the following: symptoms of ischemia: ECG changes indicative of new ischemia, development of pathological Q waves in the ECG and imaging evidence of new loss of viable myocardium or new regional wall motion abnormalities. The type of cTn (cTnT or cTnI) measured depended on the attending physician, and the cut-off value used at each institution was applied. Patients were evaluated at baseline for demographic and clinical characteristics. STEMI was diagnosed in the presence of new ST elevation at the J point in at least 2 contiguous leads ≥2 mm (0.2 mV) in men or ≥1.5 mm (0.15 mV) in women in leads V2–3 and/or ≥1 mm (0.1 mV) in other contiguous chest leads or the limb leads.^13,14 New or presumably new left bundle branch block was considered a STEMI equivalent. Urgent coronary angiography (CAG) was defined as angiography performed within 48 h of hospital admission. Optimal medical therapy (OMT) was defined as the use of necessary medications for the control of cardiovascular risk factors such as hypertension, diabetes, dyslipidemia and for the prevention of stent thrombosis (i.e., antiplatelet therapy) based on guidelines.^7–9,15

Data on the treatment and in-hospital clinical events were collected at the time of hospital discharge. Clinical 3-year follow up after the index MI was performed through a review of medical records, telephone contact, and a mailed questionnaire.¹¹

This study was conducted in accordance with the Declaration of Helsinki. The protocol was approved by the ethics committees of every participating institution.

Study Endpoints

The primary endpoint was all-cause mortality for both in-hospital and at 3 years. The principal secondary endpoint was major adverse cardiac events (MACE), defined as a composite of all-cause death, myocardial infarction, cardiac failure and stroke for both in-hospital and 3 years. Cardiac failure was defined as congestive heart failure and/or cardiogenic shock that required treatment during the index episode of hospitalization, or heart failure requiring re-hospitalization during follow up.¹¹ Stroke was defined as an acute episode of neurological dysfunction caused by focal or global brain injury, regardless of whether the cause was due to hemorrhage or infarction.¹¹ Such definitions of cardiac failure and stroke were consistent with those proposed by the ACCF/AHA task force.^16,17

Statistical Analysis

Statistical analyses were performed using SPSS V21.0 software (SPSS Inc., Chicago, IL, USA). Variables with a normal distribution are expressed as mean values±SD, and asymmetrically distributed data are given as median and interquartile range (IQR). Differences between the groups were evaluated by one-way analysis of variance (ANOVA) or the Kruskal-Wallis test for continuous variables and by a chi-squared test for categorical variables. In-hospital incidence rates of mortality and MACE were estimated by Poisson regression analysis with adjustments for age and sex. Odds ratios (OR) and 95% confidence intervals (CI) for in-hospital outcome were calculated for each factor by a logistic regression analysis. Hazard ratio (HR) and 95% CI for 3-year outcomes were estimated by a Cox proportional hazard analysis. Kaplan-Meier curves illustrated cumulative survival or event-free survival for MACE >3 years stratified by CKD stage. Numbers of patients at risk are indicated at the bottom of the Kaplan-Meier curves. All baseline variables with P<0.05 by univariable analysis were entered into a multivariable model to determine independent predictors for the endpoints.

To assess whether the predicted ability for each endpoint would improve after the addition of CKD group into a baseline model consisted of baseline variables with P<0.05 by univariate logistic analysis, we calculated C-index and net reclassification improvement (NRI). The C-index is defined as the area under receiver-operating characteristic (ROC) curves between individual predictive probabilities for the events and incidence of the events, and were compared for the baseline model and enriched models containing the significant risk factors plus CKD group.¹⁸ The NRI indicates relatively how many patients improve their predicted probabilities for the endpoints.¹⁹ Differences were considered statistically significant at P<0.05.

Results

The baseline clinical and demographic characteristics of the study cohort are summarized in Table 1. Of the 3,283 patients with AMI, 2 patients were excluded due to a missing eGFR value; the remaining 3,281 patients were enrolled (Figure 1). Of the 3,281 patients enrolled, 1,403 had CKD (defined as eGFR <60 mL/min/1.73 m²). Over two-thirds of patients presented with ST-elevation. Among the whole cohort, 93.1% underwent urgent angiography, with 85.1% receiving revascularization by PCI. The median door-to-balloon time was 75 min, with over 90% of patients achieving TIMI 3 flow at the end of the procedure.

Table 1. Baseline Patient Characteristics

	All patients (n=3,281)	No CKD eGFR >60 mL/min/1.73 m2 (n=1,878)	Moderate CKD eGFR 30–60 mL/min/1.73 m2 (n=1,073)	Severe CKD eGFR <30 mL/min/1.73 m2 (n=330)	P value
Male (%)	75.3	78.7	72.3	65.5	<0.0001
Age (years)	69±13	65±12	73±11	73±12	<0.0001
Diabetes (%)	36.4	33.8	36.9	49.5	<0.0001
Hypertension (%)	66.5	61.1	70.7	83.5	<0.0001
Dyslipidemia (%)	52.0	53.1	51.4	47.2	0.14
Smoking (%)	65.8	70.6	60.3	56.4	<0.0001
Body mass index	23.6±3.7	23.8±3.7	23.5±3.7	22.9±3.7	<0.0001
eGFR (mL/min/1.73 m2)	64.0±26.9	82.0±18.0	47.8±8.1	15.0±8.7	<0.0001
Previous history (%)
MI	12.1	9.0	15.4	18.9	<0.0001
PCI	15.3	11.8	17.9	26.3	<0.0001
CABG	2.9	1.4	3.4	10.0	<0.0001
AF	6.0	3.5	8.8	11.3	<0.0001
Stroke	11.3	8.2	13.7	20.7	<0.0001
PAD	4.6	2.1	5.5	16.8	<0.0001
Killip classification (%)					<0.0001
Class 1	75.6	85.9	63.9	55.6
Class 2	9.3	7.9	10.4	13.7
Class 3	5.4	2.9	7.6	12.5
Class 4	9.7	3.4	18.1	18.2
Door-to-admission (min)	154 (70–390)	165 (79–410)	140 (60–327)	154 (60–518)	0.0003
STEMI (%)	68.9	72.2	67.2	55.8	<0.0001
Max CK (IU/L)	1,447 (518–3,178)	1,541 (557–3,225)	1,450 (544–3,243)	908 (345–2,413)	<0.0001
Twice elevated CK (%)	78.7	79.5	79.5	71.5	0.0050
Urgent angiography (%)	93.1	95.5	91.6	84.5	<0.0001
Multi-vessel disease (%)	43.7	38.0	50.1	57.2	<0.0001
Initial TIMI 0/1 flow (%)	60.5	62.8	59.1	49.5	0.0022
Revascularization (%)					<0.0001
None	12.9	9.9	14.6	24.3
PCI	85.1	88.7	82.8	71.7
CABG	2.1	1.4	2.6	4.0
Door-to-balloon (min)	75 (52–121)	70 (50–112)	77 (53–127)	102 (67–160)	<0.0001
Final TIMI 3 flow (%)	91.8	93.3	89.3	90.6	0.0016
Length of stay (days)	14 (9–21)	13 (9–18)	16 (10–24)	15 (7–27)	<0.0001
Medication (%)
At admission
Anti-platelet agents	26.7	18.8	32.2	53.9	<0.0001
ARB	26.2	19.6	30.3	50.9	<0.0001
ACE-I	6.6	5.6	7.6	8.8	0.025
β-blockers	14.0	9.6	16.3	31.8	<0.0001
CCB	34.4	28.1	40.3	51.8	<0.0001
Nicorandil	4.5	2.5	6.3	9.7	<0.0001
Statins	23.4	19.2	27.6	33.6	<0.0001
At discharge
Anti-platelet agents	96.6	97.2	95.8	95.6	0.12
ARB	28.5	26.7	28.7	40.2	<0.0001
ACEI	52.3	56.5	51.4	26.1	<0.0001
β-blockers	68.4	67.2	70.0	70.4	0.26
CCB	22.9	19.4	25.4	37.5	<0.0001
Nicorandil	21.1	18.8	23.3	29.4	0.0001
Statins	86.9	89.8	85.3	72.9	<0.0001

ACE-I, angiotensin-converting enzyme inhibitor; AF, atrial fibrillation; ARB, angiotensin receptor blocker; CCB, calcium channel blocker; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; MI, myocardial infarction; PAD, peripheral artery disease; PCI, percutaneous coronary intervention; STEMI, ST-elevation myocardial infarction; TIMI, Thrombolysis in Myocardial Infarction.

Figure 1.

Flow-chart of the study patients. Of the 3,283 patients with AMI, 2 patients were excluded due to missing eGFR readings. The remaining 3,281 patients were enrolled. Patients were divided into 3 groups according to eGFR levels. Of the 3,281 patients, 1,878 patients were without CKD (eGFR ≥60 mL/min/1.73 m²), 1,073 patients had moderate CKD (60>eGFR≥30 mL/min/1.73 m²) and 330 patients had severe CKD (eGFR <30 mL/min/1.73 m²), including 195 hemodialysis patients. AMI, acute myocardial infarction; eGFR, estimated glomerular filtration rate.

Patients were divided into 3 groups according to eGFR levels; 1,878 patients without CKD (eGFR ≥60 mL/min/1.73 m²), 1,073 patients with moderate CKD (60>eGFR≥30 mL/min/1.73 m²) and 330 patients with severe CKD (eGFR <30 mL/min/1.73 m²), including 195 hemodialysis patients. Patients with renal dysfunction tended to be significantly older and to have a higher preponderance of cardiovascular risk factors such as diabetes and hypertension (Table 1). There was also a significantly higher prevalence of pre-existing coronary artery disease among those with CKD (Table 1). However, patients with CKD were more likely to present with non-ST-elevation myocardial infarction and as a result, were significantly less likely to receive immediate revascularization. At discharge, 96.6% of the patients received anti-platelet agents; 80.8% had either ARB or ACEI; 68.4% took β-blockers; and statins were prescribed for 86.9% of the patients.

At initial discharge from hospital, a total of 212 patients reached the in-hospital primary endpoint of all-cause mortality (Table 2). However, of these, 174 (82%) had underlying CKD, despite the fact that this group comprised only two-fifths of the study cohort (Table 2). Age- and sex-adjusted in-hospital mortality rate significantly increased from 0.014% in the no CKD group through 0.042% in the moderate CKD group to 0.084% in the severe CKD group per person-days (P<0.0001). Similar results were obtained for MACE (0.11%, 0.25% and 0.33% per person-days, respectively, P<0.0001) (Figure 2). Accordingly, at the end of 3-year follow up, a total of 389 patients met the 3-year primary endpoint of all-cause mortality (Table 2). Of these, 296 (76%) had underlying CKD, although this group consisted of only 42% of the study population (Table 2). Similarly, for the principal secondary composite endpoint of MACE, patients with CKD were significantly over-represented (Table 2).

Table 2. Incidence of In-Hospital and 3-Year Clinical Outcome in Each CKD Group

N (%)	All patients (n=3,281)	No CKD (n=1,878)	Moderate CKD (n=1,073)	Severe CKD (n=330)	P value
In-hospital
MACE	568 (17.3)	149 (7.9)	293 (27.3)	126 (38.2)	<0.0001
Mortality	212 (6.5)	38 (2.0)	103 (9.6)	71 (21.5)	<0.0001
Cardiovascular	169 (79.7)	26 (68.4)	89 (86.4)	54 (76.1)	0.035
Non-cardiovascular	43 (20.3)	12 (31.6)	14 (13.6)	17 (23.9)
Cardiac failure	493 (15.2)	127 (6.8)	263 (24.8)	103 (31.7)	<0.0001
Stroke	45 (1.4)	14 (0.7)	22 (2.1)	9 (2.7)	0.0011
3-year
MACE	897 (27.3)	296 (15.8)	410 (38.2)	191 (57.9)	<0.0001
Mortality	389 (11.9)	93 (5.09)	175 (16.3)	121 (36.7)	<0.0001
Cardiovascular	216 (55.5)	34 (33.6)	107 (61.1)	75 (62.0)	0.0009
Non-cardiovascular	159 (40.9)	54 (58.1)	64 (36.6)	41 (33.9)
Unknown	14 (3.6)	5 (5.3)	4 (2.3)	5 (4.1)
MI	100 (3.0)	26 (2.6)	28 (2.6)	24 (7.3)	<0.0001
Cardiac failure	560 (17.1)	149 (7.9)	297 (27.7)	114 (34.5)	<0.0001
Stroke	124 (3.8)	57 (3.0)	43 (4.0)	24 (7.3)	0.00087

Data are presented as n (%). CKD, chronic kidney disease; MACE, major adverse cardiac events.

Figure 2.

Age- and sex-adjusted incidence rate of in-hospital events stratified by CKD stage. A total of 212 patients reached the in-hospital primary endpoint of all-cause mortality (Left graph) and a total of 568 patients reached the in-hospital secondary composite endpoint of MACE (Right graph). The incidence of either in-hospital mortality or MACE significantly increased in proportion to the CKD stage. CKD, chronic kidney disease; MACE, major adverse cardiac events.

While cumulative survival over 3 years was significantly worse according to the degree of deterioration of CKD stages from 93.3% in the no CKD group through 79.8% in the moderate CKD group to 57.2% in the severe CKD group (Figure 3), event-free survival for MACE over 3 years has significantly deteriorated in proportion to the degree of advance of CKD stages from 80.8% in the no CKD group through 55.7% in the moderate CKD group to 35.6% in the severe CKD group (Figure 4). The differences in mortality and MACE remained highly significant after adjusting for potential confounding factors (Table 3).

Figure 3.

Kaplan-Meier curves showing cumulative survival over 3 years stratified by CKD stage. Cumulative survival over 3 years was significantly worse according to the degree of deterioration of CKD stages from 93.3% in the no CKD group through to 79.8% in the moderate CKD group to 57.2% in the severe CKD group. Numbers of patients at risk are indicated at the bottom of the figure. CKD, chronic kidney disease.

Figure 4.

Kaplan-Meier curves showing event-free survival for MACE over 3 years stratified by CKD stage. Event-free survival for MACE over 3 years significantly deteriorated in proportion to the degree of renal impairment from 80.8% in the no CKD group through to 55.7% in the moderate CKD group to 35.6% in the severe CKD group. Numbers of patients at risk are indicated at the bottom of the figure. CKD, chronic kidney disease; MACE, major adverse cardiac events.

Table 3. Predictive Value of CKD for In-Hospital and 3-Year Clinical Outcomes After AMI

In-hospital	Non-adjusted		Adjusted†
	OR (95% CI)	P value	OR (95% CI)	P value
Mortality
No	Ref.		Ref.
Moderate	5.14 (3.54–7.60)	<0.0001	2.00 (1.23–3.28)	0.0050
Severe	13.3 (8.82–20.3)	<0.0001	6.71 (3.91–11.7)	<0.0001
Severe vs. Moderate	2.51 (1.79–3.49)	<0.0001	3.17 (2.04–4.95)	<0.0001
MACE
No	Ref.		Ref.
Moderate	4.34 (3.52–5.40)	<0.0001	1.89 (1.43–2.49)	<0.0001
Severe	7.17 (5.43–9.46)	<0.0001	3.31 (2.28–4.82)	<0.0001
Severe vs. Moderate	1.64 (1.26–2.13)	0.0002	1.77 (1.24–2.53)	0.0016
3-year	Non-adjusted		Adjusted‡
	HR (95% CI)	P value	HR (95% CI)	P value
Mortality
No	Ref.		Ref.
Moderate	3.56 (2.77–4.59)	<0.0001	1.40 (0.98–2.01)	0.062
Severe	9.06 (6.92–11.9)	<0.0001	3.49 (2.19–5.37)	<0.0001
Severe vs. Moderate	2.54 (2.02–3.21)	<0.0001	2.65 (2.05–3.42)	<0.0001
MACE
No	Ref.		Ref.
Moderate	2.75 (2.37–3.19)	<0.0001	1.33 (1.09–1.63)	0.0052
Severe	5.10 (4.25–6.11)	<0.0001	2.45 (1.89–3.17)	<0.0001
Severe vs. Moderate	1.77 (1.48–2.09)	<0.0001	1.72 (1.42–2.07)	<0.0001

^†Adjusted for male, age, hypertension, dyslipidemia, previous AF, previous stroke, STEMI, Killip classification, twice CK↑, anti-platelet agents and β-blockers as variables with P<0.05 by univariate analysis for in-hospital endpoints. ^‡Adjusted for male, age, diabetes, hypertension, dyslipidemia, current smoker, previous MI, previous PCI, previous CABG, previous PAD, previous AF, previous stroke, multi-vessel disease, STEMI, Killip classification, twice CK↑, Final TIMI 3 flow, revascularization, AKI, anti-platelet agents, nicorandil and β-blockers as variables with P<0.05 by univariate analysis for 3-year endpoints. AKI, acute kidney injury; CABG, coronary artery bypass graft; CI, confidence interval; CK, creatine kinase; MACE, major adverse cardiac events; OR, odds ratio. Other abbreviations as in Table 1.

On multivariable logistic and Cox regression modelling, the presence of CKD was of independent prognostic significance and improved the discriminative performance of the baseline model, incorporating other risk markers for both the primary endpoint of all-cause mortality and the principal secondary endpoints of MACE in both in-hospital and 3-year follow up. In addition, patients with severe CKD had higher risk of mortality and MACE even compared to patients with moderate CKD (Table 3). The significantly improved C-statistic also translated into a highly significant incremental NRI (Table 4).

Table 4. Discrimination of Each Predicting Model for In-Hospital and 3-Year Clinical Outcomes After AMI Using C-Index and Net Reclassification Improvement (NRI)

	C-index (95% CI)	P value	NRI	P value
In-hospital
Mortality
Basic model†	0.877 (0.849–0.904)	Ref.
+CKD group	0.890 (0.862–0.919)	0.040	0.627	<0.0001
MACE
Basic model†	0.820 (0.798–0.842)	Ref.
+CKD group	0.830 (0.808–0.851)	0.011	0.306	<0.0001
3-year
Mortality
Basic model‡	0.815 (0.788–0.841)	Ref.
+CKD group	0.831 (0.806–0.857)	0.013	0.486	<0.0001
MACE
Basic model‡	0.731 (0.708–0.755)	Ref.
+CKD group	0.740 (0.717–0.764)	0.046	0.331	<0.0001

^†Model includes male, age, hypertension, dyslipidemia, previous AF, previous stroke, STEMI, Killip classification, twice CK↑, anti-platelet agents and β-blockers. ^‡Model includes male, age, diabetes, hypertension, dyslipidemia, current smoker, previous MI, previous PCI, previous CABG, previous PAD, previous AF, previous stroke, multi-vessel disease, STEMI, Killip classification, twice CK↑, Final TIMI 3 flow, revascularization, AKI, anti-platelet agents, nicorandil and β-blockers. Abbreviations as in Tables 1,3.

Discussion

We found that despite advances in medical therapy, and improvements in the availability and delivery of mechanical reperfusion therapy in the contemporary PCI era, the presence of CKD continues to portend a significantly increased risk of adverse outcomes for all the endpoints examined. This prognostic significance was retained even after adjusting for known confounders. CKD also improved risk stratification when used to enrich a model with other established risk markers and, importantly, significantly improved reclassification metrics.

The association between CKD and adverse outcomes exhibited a dose-response relationship, with progressively worsening renal dysfunction being associated with a commensurately worse rate of adverse events. The underlying pathophysiologic basis for this association remains incompletely understood, but this dose-response behavior provides persuasive support for a causal link.

Interestingly, the immediate drop of Kaplan-Meier curves in severe CKD was driven by the fact that in-hospital mortality and MACE significantly deteriorated from 7.9% and 2.0% in the no CKD group through to 27.3% and 9.6% in the moderate CKD group to 38.2% and 21.5% in the severe CKD group (Table 2). Although the precise mechanisms responsible for the association between in-hospital cardiac events and the degree of CKD are unknown, several mechanisms have been implicated. Firstly, a higher incidence of acute kidney injury could confer increased in-hospital mortality.^20,21 While acute kidney injury is associated with worse long-term outcomes after MI, this effect is modified by baseline CKD status.²⁰ Secondly, it is also recognized that patients with CKD and AMI experience a higher incidence of complications such as bleeding and contrast nephropathy, which may have a deleterious impact on clinical outcome.^22–24 Thirdly, the location of the coronary culprit lesion in AMI is more proximal in patients with CKD, possibly leading to higher event rates or threatening a larger myocardial volume.²⁵ Finally, despite being among the highest-risk subset of patients with AMI, patients with advanced CKD have been generally excluded from randomized trials evaluating strategies that impact survival with AMI.²⁴ The resulting dearth of evidence on optimal treatment strategies for such patients may thereby result in worse outcomes.

CKD is strongly associated with other cardiovascular risk factors such as diabetes and hypertension.^1,2,23,26 The latter both causes and/or contributes to CKD, but can also result from it. In keeping with this, CKD was strongly associated with a greater preponderance of cardiovascular risk factors.² Furthermore, CKD patients were also significantly more likely to have pre-existing coronary artery disease prior to their index presentation with AMI. Hinting at the presence of more advanced underlying atherosclerosis, significantly fewer patients with CKD achieved TIMI 3 flow. However, despite adjusting for these pleiotropic confounding factors, the association between CKD and adverse events retained independent prognostic significance.

Interestingly, patients with CKD were less likely to present with STEMI. The higher incidence of NSTEMI and concerns about risks of inducing contrast nephropathy may explain why rates of urgent angiography were lower in our cohort among this ostensibly higher risk subgroup.⁹ It may also suggest that the mechanisms underlying ACS in this cohort may be pathologically distinct. We speculate that plaque erosion may be a more predominant mechanism in the CKD group, in which patients tended to be older and have more established atherosclerosis, whereas plaque rupture may be more common in younger non-CKD patients where less mature plaques that are more vulnerable to rupture may be responsible.^27,28 The higher prevalence of STEMI in the non-CKD group may provide some circumstantial support for this, but the underlying mechanisms require further study.

Patients with CKD were more likely to experience acute heart failure as part of their presentation with AMI (Table 2). This is despite experiencing lower peak enzyme rises (Table 1) compared to patients without CKD. This may reflect both pre-existing LV systolic dysfunction, the greater severity of the underlying coronary disease, and the more precarious fluid balance and handling seen with progressively lower renal clearance.

The risk stratification of patients presenting with AMI and other acute coronary syndromes remains an important challenge.⁶ In an era where the costs of medical care are escalating in all healthcare settings and models of care delivery are evolving, the appropriate identification and triage of patients to early intervention and revascularization is an important goal both for improving patient outcomes and reducing healthcare costs.^8,9,29 Similarly, identifying patients at lower risk who might benefit from early discharge could reduce length of hospitalization. Clinical scoring systems for achieving these goals must be simple to apply at the bedside and ideally rely on data that are already collected as part of routine care. In this context, the presence of CKD is relatively easy to determine with routine laboratory testing and based on our data, should continue to remain an important component of any risk stratification tools, despite advances in clinical care.

Our work also highlights the need for further research to elucidate the mechanisms by which CKD worsens outcomes in patients with AMI. While recent data suggest that the incidence of cardiac events in this high-risk cohort has been falling in recent years, probably as a result of better risk factor control including OMT and modern primary PCI, the development of CKD nevertheless retains ominous prognostic significance that has not yet been sufficiently ameliorated by improvements in cardiovascular knowledge and care.

Study Limitations

Our study has a number of limitations. Firstly, it was conducted in one country (Japan). While this has the advantage of removing the potential influence of differences between populations and healthcare systems on outcomes, it may also limit the generalizability of our results. Secondly, the study represents observational data with all the potential limitations inherent to registry studies, in particular, referral bias and potential bias in the ascertainment of endpoints. Finally, Tonelli et al revealed that the presence and severity of proteinuria was significantly associated with graded increases in the risk of clinical outcomes for both lower and higher eGFR, while Ota et al reported that proteinuria may be a prognostic marker for long-term mortality.^30,31 The presence of proteinuria could be some marker for the prediction of cardiac events. However, unfortunately, we did not collect data on proteinuria in the current study.

Conclusions

CKD remains associated with adverse outcomes in patients presenting with AMI, despite advances in the care of these patients prior to and after presentation. The presence of CKD retained independent prognostic significance even after adjusting for confounders and significantly improved model performance. CKD should therefore remain a key component of any model used to risk stratify patients presenting with AMI.

Disclosures

Y.O., K. Kimura, J.A., T.N., W.S. Y. Saito, T.I., K. Tsujita, S.Y., H.I., H.O. and M.I. are members of Circulation Journal’s Editorial Team.

IRB Information

The present study was approved by the National Cerebral and Cardiovascular Center Institutional Review Board for Clinical Research (Reference number: M23-084).

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